link
data.matrix <- matrix(nrow=100, ncol=10)
colnames(data.matrix) <- c(
paste("wt", 1:5, sep=""),
paste("ko", 1:5, sep=""))
rownames(data.matrix) <- paste("gene", 1:100, sep="")
for (i in 1:100) {
wt.values <- rpois(5, lambda=sample(x=10:1000, size=1))
ko.values <- rpois(5, lambda=sample(x=10:1000, size=1))
data.matrix[i,] <- c(wt.values, ko.values)
}
tdata <- t(data.matrix)
head(tdata)
## gene1 gene2 gene3 gene4 gene5 gene6 gene7 gene8 gene9 gene10 gene11
## wt1 682 14 448 674 325 379 31 24 214 829 11
## wt2 706 8 469 661 316 379 32 29 243 842 10
## wt3 671 13 500 680 367 368 36 26 234 883 8
## wt4 662 15 443 664 367 366 31 21 204 817 12
## wt5 690 10 442 649 343 363 41 25 209 876 11
## ko1 444 164 222 990 736 290 656 538 198 602 848
## gene12 gene13 gene14 gene15 gene16 gene17 gene18 gene19 gene20 gene21
## wt1 899 252 657 502 863 33 335 581 770 60
## wt2 900 250 677 440 858 39 304 587 748 40
## wt3 919 263 711 449 885 39 310 574 731 56
## wt4 909 239 678 463 860 39 336 554 754 55
## wt5 959 261 690 446 926 34 331 606 747 56
## ko1 548 283 832 922 816 443 498 248 411 694
## gene22 gene23 gene24 gene25 gene26 gene27 gene28 gene29 gene30 gene31
## wt1 239 689 772 902 357 721 23 562 567 83
## wt2 240 682 860 927 418 726 41 566 599 61
## wt3 234 662 828 844 363 703 29 575 589 82
## wt4 256 668 868 894 379 737 42 579 538 74
## wt5 221 668 792 874 430 682 44 557 559 78
## ko1 351 482 900 743 457 815 75 1013 79 711
## gene32 gene33 gene34 gene35 gene36 gene37 gene38 gene39 gene40 gene41
## wt1 427 270 367 821 531 691 438 615 444 791
## wt2 438 272 369 785 500 703 458 567 407 852
## wt3 435 285 371 796 565 671 398 605 411 763
## wt4 477 270 355 812 534 704 454 615 408 782
## wt5 401 248 359 797 548 667 426 674 438 812
## ko1 477 747 349 434 486 595 557 132 82 710
## gene42 gene43 gene44 gene45 gene46 gene47 gene48 gene49 gene50 gene51
## wt1 750 639 348 915 309 680 259 770 352 489
## wt2 748 655 351 914 337 620 297 685 386 464
## wt3 757 652 374 909 311 672 284 765 368 493
## wt4 759 668 368 916 321 633 309 769 390 501
## wt5 771 647 309 930 337 698 274 759 355 478
## ko1 654 550 833 831 890 450 781 297 546 665
## gene52 gene53 gene54 gene55 gene56 gene57 gene58 gene59 gene60 gene61
## wt1 598 311 258 192 727 337 122 110 637 809
## wt2 594 296 287 203 722 337 103 103 688 840
## wt3 532 307 266 187 689 363 100 116 698 815
## wt4 579 320 283 194 679 330 81 120 711 852
## wt5 532 335 269 199 722 328 101 123 696 767
## ko1 736 603 730 786 209 240 842 1021 836 634
## gene62 gene63 gene64 gene65 gene66 gene67 gene68 gene69 gene70 gene71
## wt1 616 366 365 813 784 522 672 347 872 185
## wt2 621 319 333 860 805 546 769 390 836 147
## wt3 641 331 322 799 793 508 726 385 835 170
## wt4 644 310 361 822 811 538 707 357 843 189
## wt5 637 333 326 788 813 507 739 372 789 163
## ko1 496 984 1066 888 17 259 781 168 521 897
## gene72 gene73 gene74 gene75 gene76 gene77 gene78 gene79 gene80 gene81
## wt1 538 954 469 587 67 101 763 749 910 613
## wt2 549 867 470 563 74 125 828 778 942 612
## wt3 489 895 498 621 60 94 735 687 1001 587
## wt4 482 952 446 619 66 118 776 742 928 573
## wt5 537 878 438 606 55 107 757 657 959 581
## ko1 523 345 747 649 77 944 693 15 51 526
## gene82 gene83 gene84 gene85 gene86 gene87 gene88 gene89 gene90 gene91
## wt1 128 136 367 260 368 444 774 519 288 297
## wt2 108 102 360 297 345 404 845 467 275 291
## wt3 99 110 380 256 380 387 812 521 263 264
## wt4 118 119 366 230 375 433 790 530 260 258
## wt5 149 107 366 250 339 434 773 494 268 283
## ko1 271 830 249 453 136 18 796 163 220 633
## gene92 gene93 gene94 gene95 gene96 gene97 gene98 gene99 gene100
## wt1 582 92 442 923 967 696 369 780 423
## wt2 563 80 442 904 977 694 357 771 433
## wt3 573 88 437 924 923 686 378 796 408
## wt4 578 70 409 899 988 720 397 766 426
## wt5 517 89 466 913 1006 778 394 749 430
## ko1 390 161 701 672 123 737 816 702 222
head(data.matrix)
## wt1 wt2 wt3 wt4 wt5 ko1 ko2 ko3 ko4 ko5
## gene1 682 706 671 662 690 444 418 447 464 410
## gene2 14 8 13 15 10 164 179 153 141 159
## gene3 448 469 500 443 442 222 218 251 232 237
## gene4 674 661 680 664 649 990 904 919 884 903
## gene5 325 316 367 367 343 736 702 709 726 696
## gene6 379 379 368 366 363 290 314 296 276 290
pca <- prcomp(t(data.matrix), scale=TRUE)
summary(pca)
## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6
## Standard deviation 9.3818 1.77024 1.42646 1.3306 1.23248 1.07882
## Proportion of Variance 0.8802 0.03134 0.02035 0.0177 0.01519 0.01164
## Cumulative Proportion 0.8802 0.91152 0.93187 0.9496 0.96476 0.97640
## PC7 PC8 PC9 PC10
## Standard deviation 0.96092 0.89955 0.79205 3.687e-15
## Proportion of Variance 0.00923 0.00809 0.00627 0.000e+00
## Cumulative Proportion 0.98563 0.99373 1.00000 1.000e+00
pca$rotation
## PC1 PC2 PC3 PC4
## gene1 -0.10556159 -0.0421504030 -0.0557228266 0.0259194177
## gene2 0.10573872 0.0207481068 0.0013904952 -0.0169430817
## gene3 -0.10544606 -0.0244274884 0.0257177663 0.0078329602
## gene4 0.10431172 0.0025312632 0.0112621854 0.0506631400
## gene5 0.10610598 0.0101549324 0.0166804357 0.0626512834
## gene6 -0.10356908 -0.0160354466 -0.0187685781 -0.0852604890
## gene7 0.10626136 -0.0108835377 -0.0011838748 0.0239803742
## gene8 0.10637336 -0.0031869489 -0.0142360035 0.0053183405
## gene9 0.01508732 -0.2587194411 -0.0458340905 -0.3188903215
## gene10 -0.10486604 0.0036433007 -0.0291485482 0.0520384413
## gene11 0.10650050 0.0016109374 -0.0021037596 0.0059457294
## gene12 -0.10560365 0.0251082675 0.0004119449 -0.0013953103
## gene13 0.09113077 -0.0517730356 -0.1617072893 0.2516914659
## gene14 0.10393936 -0.0052875190 0.0104146802 0.0813333385
## gene15 0.10592585 0.0065475880 -0.0017959566 0.0428845707
## gene16 -0.05975260 0.3440133704 -0.1945658138 -0.2050250073
## gene17 0.10635107 -0.0049608455 -0.0001535922 0.0044717932
## gene18 0.10410131 0.0223988571 -0.0146929166 0.1064774666
## gene19 -0.10627027 0.0052176933 -0.0321130670 -0.0144658096
## gene20 -0.10632085 -0.0006435921 0.0070163084 -0.0047984011
## gene21 0.10611896 -0.0029379504 -0.0273266196 0.0496980808
## gene22 0.10116047 -0.0541292100 -0.0343035086 0.0998260227
## gene23 -0.10541809 0.0057701360 0.0154188730 -0.0546182693
## gene24 0.09063823 -0.1397095836 0.1326768833 -0.0989659786
## gene25 -0.09844459 -0.1049456790 -0.0724162196 -0.1020150304
## gene26 0.08499020 0.0766355968 -0.1612621674 -0.3196776116
## gene27 0.09874203 -0.0524613586 0.1777039580 -0.1523357655
## gene28 0.09975550 0.0436701795 -0.0269037121 -0.1637253164
## gene29 0.10629415 -0.0044468119 -0.0024224063 0.0327332346
## gene30 -0.10631525 -0.0239487514 0.0006777606 -0.0161973084
## gene31 0.10639858 -0.0002530170 -0.0115059351 0.0310466736
## gene32 0.08432073 -0.1062223327 0.3550494939 -0.0705410470
## gene33 0.10599640 -0.0025909629 -0.0040088332 0.0041751665
## gene34 -0.09372548 -0.0820813958 -0.0213992367 0.0600918142
## gene35 -0.10628242 0.0055874146 0.0295752127 0.0093036792
## gene36 -0.08802190 0.1779263094 0.0396391874 0.1703590469
## gene37 -0.08916559 -0.0535619170 0.0038239523 -0.1363705285
## gene38 0.10258829 -0.0380620550 -0.0137076564 -0.0953799014
## gene39 -0.10595666 0.0502442334 -0.0071701258 0.0005750266
## gene40 -0.10630817 0.0192980982 -0.0013250382 -0.0103907175
## gene41 -0.09508663 -0.1289745507 -0.2121459775 -0.1327372313
## gene42 -0.10002403 0.0437595747 -0.0981679991 0.0478537316
## gene43 -0.10340193 -0.0059301801 0.0157670289 -0.0338569127
## gene44 0.10603196 -0.0186336810 0.0228297599 0.0231104820
## gene45 -0.09757410 0.0019357100 0.0499354906 0.0129553276
## gene46 0.10623968 -0.0004895773 -0.0322379065 -0.0047268320
## gene47 -0.10197771 0.1021893528 0.0137435929 -0.0374630904
## gene48 0.10624879 -0.0209998358 -0.0013450778 0.0272261427
## gene49 -0.10594131 0.0314745987 0.0239523847 0.0516413311
## gene50 0.10467547 -0.0369460107 0.0775154372 -0.0655472857
## gene51 0.10464052 0.0349929437 0.0108735647 0.0723103045
## gene52 0.10227552 -0.0911144963 0.0158329217 0.0107012259
## gene53 0.10572090 0.0577463406 0.0083008919 -0.0325758004
## gene54 0.10631276 -0.0110889009 0.0061180569 0.0011170545
## gene55 0.10621612 -0.0122192395 -0.0341797820 0.0369901704
## gene56 -0.10640086 -0.0049122389 -0.0256650599 -0.0195200651
## gene57 -0.10417734 -0.0466573025 0.0446155593 0.0589969279
## gene58 0.10637836 0.0006953797 -0.0182324967 0.0115806056
## gene59 0.10639660 0.0132621798 -0.0102287745 0.0099314227
## gene60 0.10140712 0.0440620754 0.0380560078 -0.0243083931
## gene61 -0.09836676 -0.1497580428 0.0544200824 0.0893231445
## gene62 -0.10486284 0.0011856468 0.0317829874 0.0545252043
## gene63 0.10630409 0.0112337984 -0.0076481154 0.0076213140
## gene64 0.10622580 -0.0013679530 0.0171124448 -0.0027957631
## gene65 0.07680151 -0.2256937569 0.0623863580 -0.2510135717
## gene66 -0.10644399 0.0029012703 0.0069527275 -0.0176645640
## gene67 -0.10585202 -0.0199876504 0.0287597806 -0.0612677980
## gene68 0.07510557 -0.1612819903 -0.3002698323 -0.0451651980
## gene69 -0.10542128 -0.0173354764 0.0009685020 -0.0567048396
## gene70 -0.10519254 -0.0293793344 0.0648875286 -0.0094629600
## gene71 0.10634360 0.0032162186 0.0017749006 0.0376466985
## gene72 0.01882213 -0.2077581267 -0.5683212645 0.0235589238
## gene73 -0.10609094 0.0097381219 0.0480685826 0.0122987546
## gene74 0.10574230 -0.0294536469 0.0203654108 0.0300279209
## gene75 0.08444863 0.1923059709 0.2534510686 -0.1004997325
## gene76 0.07929629 -0.1445791751 0.2077836421 -0.3526721913
## gene77 0.10646477 -0.0137462869 -0.0153382492 0.0247675981
## gene78 -0.09524695 -0.1274246353 -0.0738205336 -0.1243738844
## gene79 -0.10606921 -0.0366628008 0.0246777830 -0.0320558016
## gene80 -0.10638588 0.0054450397 0.0105623360 -0.0104717788
## gene81 -0.08600602 -0.0643393248 0.0248887948 -0.3263069601
## gene82 0.10351919 0.0710293052 -0.0918919172 0.0039416549
## gene83 0.10636071 -0.0076130352 -0.0037665287 0.0271382056
## gene84 -0.10287625 0.0499084604 -0.0122489575 0.0209218278
## gene85 0.10173729 -0.0450186622 -0.0716280898 -0.0702813334
## gene86 -0.10557624 0.0093665077 0.0396143690 0.0329433427
## gene87 -0.10620296 0.0176644227 0.0067478501 -0.0131328562
## gene88 -0.03605430 -0.4646573771 -0.0634233052 0.0916291580
## gene89 -0.10604115 0.0255607792 0.0530675297 0.0230311236
## gene90 -0.10234180 0.0022991417 -0.0314755440 -0.0421367449
## gene91 0.10568679 0.0083368128 -0.0424684715 -0.0227203139
## gene92 -0.10353843 -0.0611567955 0.1135344554 0.0473995629
## gene93 0.10292872 0.0173536250 -0.0062411610 -0.0264710050
## gene94 0.10511157 0.0144473382 -0.0845885395 0.0047199636
## gene95 -0.10572842 0.0246675543 -0.0066649858 -0.0120002776
## gene96 -0.10632064 0.0091854009 -0.0033428331 -0.0215180851
## gene97 0.02623869 0.4364446726 -0.2216418371 -0.2819894364
## gene98 0.10607019 0.0210911626 -0.0159949738 0.0410304662
## gene99 -0.09663728 -0.0893190502 0.0594852359 0.0877502870
## gene100 -0.10563872 -0.0271600266 -0.0255112099 -0.0068283767
## PC5 PC6 PC7 PC8
## gene1 0.0509811188 -0.008697572 -0.0325659585 0.0158875714
## gene2 -0.0403348743 0.014440407 0.0635618629 -0.0667496002
## gene3 -0.0312309137 -0.062744576 -0.0597038679 0.0806717073
## gene4 0.0728057181 0.013306191 0.0064283865 -0.0493156906
## gene5 0.0027321381 -0.030847036 0.0056850792 -0.0066830321
## gene6 -0.0641365984 0.047986328 0.1305120304 -0.0699231204
## gene7 -0.0085379103 0.012371740 -0.0523527347 0.0052093286
## gene8 -0.0427473323 0.015442618 0.0084957745 0.0216055746
## gene9 -0.5911797326 -0.137737246 -0.1573281973 0.1114750204
## gene10 0.0395786436 -0.084748048 -0.0948016371 -0.0826921624
## gene11 0.0039031576 0.011938988 -0.0079286074 -0.0309419227
## gene12 0.0602341323 -0.045704682 -0.0795843419 -0.0396337072
## gene13 -0.1512334203 -0.046305346 -0.2030576134 0.0153229192
## gene14 0.0050521984 -0.123900176 -0.1422654469 0.0219073819
## gene15 0.0129145678 0.073223108 0.0193287389 0.0128668257
## gene16 -0.2556006801 -0.153498790 -0.0662700058 0.2004539269
## gene17 -0.0324252750 0.014129517 -0.0166565856 0.0451997618
## gene18 0.0718885155 0.067866858 0.0096127502 0.1060669440
## gene19 0.0243102872 -0.012187717 -0.0421807629 -0.0275515251
## gene20 0.0323423387 0.034114677 0.0052174212 0.0371313109
## gene21 -0.0264438188 0.017415195 0.0340883169 0.0217997601
## gene22 -0.0827252980 0.008937201 0.2525987195 -0.0196237772
## gene23 0.0569570316 0.052454389 -0.0253180179 0.0811118441
## gene24 0.0611046934 -0.291665445 0.1838718931 0.1690382406
## gene25 -0.0285460852 0.084753806 0.2187084855 -0.1511219272
## gene26 0.1781734141 -0.150151427 -0.1627347564 0.1196726052
## gene27 0.0572964293 0.076704730 0.0509262272 -0.1198462317
## gene28 0.1227647218 -0.171419951 0.0404958513 -0.0988761226
## gene29 0.0101664770 -0.002819164 0.0291053823 -0.0215421922
## gene30 0.0073815440 -0.022978666 -0.0444721449 -0.0164776854
## gene31 -0.0217371796 0.015524351 0.0056509399 -0.0260361795
## gene32 0.0509682076 -0.038687735 0.0375014448 0.0991801381
## gene33 -0.0424091175 0.005198625 0.0535545177 -0.0396545487
## gene34 0.0737093379 0.029236357 -0.2018651692 0.1859067785
## gene35 0.0392666816 0.018216150 -0.0187569731 0.0008405101
## gene36 -0.2075729016 -0.166345966 0.0336561997 -0.2667751562
## gene37 -0.1197423969 0.081592246 0.4182677092 0.2880772564
## gene38 0.1213471771 0.080660682 0.1546788281 0.0264644409
## gene39 0.0237310441 -0.013215351 -0.0245668527 -0.0091984411
## gene40 0.0212247460 0.027634501 -0.0346442742 -0.0330071216
## gene41 0.0791658512 -0.016897033 0.0758599981 -0.1054020720
## gene42 -0.1550451444 -0.069632224 0.1870135748 0.0286866871
## gene43 -0.0315692772 -0.103453105 0.1951690379 -0.0938269103
## gene44 -0.0448644021 0.012139390 0.0069247606 0.0704963420
## gene45 0.2152646502 -0.007136010 -0.2791262833 0.0065709868
## gene46 -0.0413045118 0.001060162 0.0418438651 -0.0150653625
## gene47 -0.0703677198 0.049966518 -0.1872042444 0.0133232693
## gene48 -0.0091451901 -0.012100562 0.0063411635 0.0468029743
## gene49 -0.0148611161 0.002301887 0.0224433787 -0.0226683722
## gene50 0.0356679619 -0.044132314 -0.0531653446 -0.0548919213
## gene51 -0.0137380001 0.019762769 0.1034103389 0.0910427463
## gene52 0.0054839769 0.145651260 0.0033727891 0.1242228373
## gene53 0.0279483761 0.012811421 -0.0192612812 0.0035218034
## gene54 0.0426401632 -0.008017560 -0.0229158741 -0.0355831390
## gene55 -0.0181998718 0.009284150 0.0346486991 -0.0034034529
## gene56 0.0040663969 0.012166102 -0.0004104864 -0.0379947583
## gene57 -0.0887030985 -0.067337381 -0.0874279711 -0.0645587543
## gene58 -0.0159920938 0.029134030 0.0052834529 -0.0179344773
## gene59 -0.0046060192 0.012412878 0.0138874456 0.0343649989
## gene60 0.1012129608 -0.190942958 -0.0030120341 0.1732006915
## gene61 -0.0335470648 -0.036591924 0.1554168421 0.0752855050
## gene62 0.0476984712 -0.098354327 -0.0232260262 -0.0752749977
## gene63 -0.0101434302 0.047266584 -0.0179090838 0.0047362666
## gene64 0.0045814430 0.033195507 -0.0035302284 -0.0774025655
## gene65 0.0616574223 -0.005295725 0.0816990540 -0.4830370086
## gene66 0.0235276572 -0.026418533 0.0018970677 -0.0114070490
## gene67 0.0447450336 -0.007797256 0.0326255145 -0.0102639652
## gene68 0.0455330264 -0.440561215 0.0521469848 -0.0073399536
## gene69 0.0049658115 -0.091256448 -0.0491706478 -0.0534105745
## gene70 0.0359062847 0.041252592 -0.0121210967 -0.1114516760
## gene71 0.0035316017 0.027303853 0.0005804455 0.0376932152
## gene72 0.0081923911 0.341810182 -0.0889426711 -0.0635846558
## gene73 0.0322171237 0.033549691 0.0301670688 -0.0128177117
## gene74 -0.0400130184 0.006916136 -0.0591805964 -0.0064633768
## gene75 -0.1468051350 -0.134233779 -0.1127161292 -0.2079875679
## gene76 0.0631219433 0.169346142 -0.1613855513 0.1083148155
## gene77 0.0043066809 0.008943114 0.0046143095 -0.0040907504
## gene78 0.2334207846 -0.002373430 0.1209652601 0.0939640998
## gene79 0.0312873504 0.017309693 0.0245196192 -0.0073399182
## gene80 -0.0013228671 -0.048207807 -0.0246634484 -0.0031484490
## gene81 -0.1855554888 0.246266558 -0.1395228577 0.0035473259
## gene82 0.0163838837 0.050716357 0.0863837803 -0.1274485999
## gene83 -0.0249991111 0.030668120 -0.0022994533 -0.0190025507
## gene84 0.0045200673 -0.026691950 0.1006835176 0.1535852117
## gene85 0.0349289983 0.012628893 0.0135149973 -0.1031924880
## gene86 -0.0052517386 -0.014728424 0.0881305297 0.0000486805
## gene87 0.0389263467 0.031026263 0.0133161856 -0.0230360301
## gene88 0.1214548297 -0.350930771 -0.1359516499 -0.0148361984
## gene89 0.0210725957 -0.003500205 0.0194660270 -0.0218104403
## gene90 0.0951658488 0.154273335 -0.0159408251 -0.0334513021
## gene91 -0.0480108575 0.053744762 0.0403248128 0.0414676697
## gene92 0.0738990243 0.042835068 -0.0563440357 0.0374163726
## gene93 -0.0694542950 0.060819965 -0.1576110060 -0.1944970444
## gene94 -0.0720689498 0.014576931 0.0288011666 -0.0550922203
## gene95 -0.0575221340 0.016412267 0.0146356738 0.0945634791
## gene96 0.0457112312 -0.009451364 0.0070434462 -0.0006282281
## gene97 0.2004768030 -0.133372903 0.0851956456 -0.1095302769
## gene98 0.0002465353 0.002377243 0.0318507560 0.0688457150
## gene99 -0.2229793055 -0.019963704 0.0912813342 -0.2132883093
## gene100 0.0040627529 -0.009838983 0.0242601151 -0.0612751442
## PC9 PC10
## gene1 -0.037796166 -0.2225145869
## gene2 0.079705703 -0.0306452709
## gene3 0.073522725 -0.1044842108
## gene4 0.208198209 0.1048768796
## gene5 0.006339721 -0.0374330820
## gene6 0.143187322 -0.2505626224
## gene7 -0.055183941 -0.0126246167
## gene8 -0.009445943 0.0321289283
## gene9 0.004934811 -0.0592237902
## gene10 0.038671249 -0.0503918069
## gene11 0.029993377 -0.0164591758
## gene12 -0.046695489 -0.0489580618
## gene13 -0.177481759 0.0263008667
## gene14 -0.012766811 -0.0924654104
## gene15 0.057037673 -0.0710981287
## gene16 0.017592744 0.1556157890
## gene17 -0.031283980 0.0155997278
## gene18 -0.051371102 0.0040954087
## gene19 -0.012346876 0.0330823735
## gene20 -0.035813326 -0.0662893316
## gene21 0.004722280 0.0078069500
## gene22 -0.023104529 0.1338396276
## gene23 0.055613401 0.0870585272
## gene24 -0.075320263 0.3069645740
## gene25 -0.133195944 -0.1297146898
## gene26 -0.048277087 -0.0351491513
## gene27 0.056543160 0.0045489492
## gene28 -0.065487802 0.0970880502
## gene29 0.059698818 -0.0403790830
## gene30 0.014383667 -0.0424312251
## gene31 0.006091929 -0.0245941840
## gene32 -0.305556516 0.0721188307
## gene33 0.083035343 -0.0289460779
## gene34 0.443741657 0.2462763104
## gene35 -0.032571136 0.0171296674
## gene36 0.112719830 0.0371632486
## gene37 0.008252431 -0.0237932496
## gene38 0.007708502 0.0551966457
## gene39 -0.058334805 0.0121304844
## gene40 -0.023402791 0.0282761445
## gene41 -0.090434824 0.0994832534
## gene42 -0.152616158 -0.2286811557
## gene43 0.001412422 -0.0751516011
## gene44 -0.008149236 0.0189280752
## gene45 -0.150434514 -0.0534254188
## gene46 0.001482313 -0.0396984371
## gene47 -0.098879589 0.0741026111
## gene48 -0.050092898 0.0385241714
## gene49 -0.055120775 0.0386831850
## gene50 -0.059624197 -0.0536765905
## gene51 0.094263778 0.1225522521
## gene52 -0.156383303 -0.0821829098
## gene53 0.056873458 0.0263624385
## gene54 0.024372121 0.0097212145
## gene55 0.001518812 0.0063105986
## gene56 -0.011058961 0.0042173934
## gene57 0.009027199 -0.1393892728
## gene58 0.046844227 -0.0224865836
## gene59 0.046022379 0.0149491144
## gene60 0.063363284 0.0009830317
## gene61 -0.210289007 0.1512254468
## gene62 -0.089375567 0.0689555815
## gene63 0.051386638 -0.0399688181
## gene64 0.005612978 -0.0252429499
## gene65 0.039004475 0.0149751042
## gene66 -0.021354449 0.0101321957
## gene67 0.006392322 0.0226071244
## gene68 0.072671714 -0.2626490105
## gene69 0.037654821 0.0287197519
## gene70 0.027663262 0.0064042791
## gene71 0.005726213 0.0195374247
## gene72 -0.213892599 0.1908295625
## gene73 -0.017988102 0.0071672379
## gene74 0.088518431 -0.0965238803
## gene75 -0.108346816 0.1085833303
## gene76 -0.005364649 -0.2320819463
## gene77 -0.006214708 -0.0290336754
## gene78 0.117870040 0.0435864293
## gene79 -0.006921544 -0.0028341557
## gene80 0.005972088 -0.0120686739
## gene81 0.092018403 0.2579299436
## gene82 0.022645062 0.0128766680
## gene83 -0.026165177 0.0029621835
## gene84 0.219636146 -0.0677282232
## gene85 0.289587521 -0.0747127828
## gene86 0.098308900 0.0010588056
## gene87 -0.054234014 0.0206001066
## gene88 0.068571997 0.1523992290
## gene89 0.013752093 -0.0191263834
## gene90 0.219907262 -0.0471076079
## gene91 0.060618643 -0.0527124893
## gene92 0.002598054 0.0266747948
## gene93 0.009917979 -0.0533803975
## gene94 0.038374892 -0.0151866742
## gene95 0.041159134 -0.1432165062
## gene96 -0.031026621 -0.0134034581
## gene97 -0.075387360 0.1334570665
## gene98 0.008289848 0.0540232888
## gene99 0.136512725 0.3026739712
## gene100 -0.128254514 0.0173264974
pca$x
## PC1 PC2 PC3 PC4 PC5 PC6
## wt1 -9.370823 0.079904160 0.24497886 0.54653184 -0.2975869 2.777986577
## wt2 -8.741505 -3.622653102 -1.24528906 -1.80750487 0.4852468 -0.394818993
## wt3 -9.090201 -0.011179552 1.22421644 1.31699663 -1.5933882 -1.339842142
## wt4 -8.430157 0.511531009 2.27687400 0.05905742 1.0831721 -0.549020895
## wt5 -8.839979 3.048001224 -2.40790089 -0.21331091 0.4502512 -0.574948837
## ko1 9.230789 0.002167775 0.03072004 0.82944925 2.3341824 -0.218583571
## ko2 8.693171 0.227411076 -0.59608274 -0.75460902 -1.9731572 -0.152755368
## ko3 8.422925 0.503297082 -1.03306982 0.77878294 -0.1341067 0.183484188
## ko4 8.842555 -1.941512862 -0.15953149 1.67602419 -0.2465121 0.004485865
## ko5 9.283223 1.203033190 1.66508465 -2.43141746 -0.1081015 0.264013175
## PC7 PC8 PC9 PC10
## wt1 -0.13211666 -0.27628392 0.25030462 1.481454e-15
## wt2 0.01455959 0.23430161 0.22339914 2.137179e-15
## wt3 -0.91801987 0.08373687 0.90644455 2.081668e-15
## wt4 1.54933894 0.11978434 -0.79622660 3.004541e-15
## wt5 -0.52869060 -0.19740582 -0.61560816 3.459039e-15
## ko1 -0.22212116 -1.04129878 1.03923996 4.066192e-15
## ko2 1.33659274 -1.33299623 0.09671415 3.620368e-15
## ko3 0.91153448 1.99859512 0.54252279 3.594347e-15
## ko4 -0.80428094 -0.06888289 -1.51594111 3.086073e-15
## ko5 -1.20679652 0.48044969 -0.13084934 4.291706e-15
library(ggbiplot)
## Loading required package: ggplot2
## Loading required package: plyr
## Loading required package: scales
## Loading required package: grid
ggbiplot(pca)
ggbiplot(pca, labels=rownames(tdata))
## plot pc1 and pc2
plot(pca$x[,1], pca$x[,2])
## make a scree plot
pca.var <- pca$sdev^2
pca.var.per <- round(pca.var/sum(pca.var)*100, 1)
barplot(pca.var.per, main="Scree Plot", xlab="Principal Component", ylab="Percent Variation")
library(ggplot2)
pca.data <- data.frame(Sample=rownames(pca$x),
X=pca$x[,1],
Y=pca$x[,2])
pca.data
## Sample X Y
## wt1 wt1 -9.370823 0.079904160
## wt2 wt2 -8.741505 -3.622653102
## wt3 wt3 -9.090201 -0.011179552
## wt4 wt4 -8.430157 0.511531009
## wt5 wt5 -8.839979 3.048001224
## ko1 ko1 9.230789 0.002167775
## ko2 ko2 8.693171 0.227411076
## ko3 ko3 8.422925 0.503297082
## ko4 ko4 8.842555 -1.941512862
## ko5 ko5 9.283223 1.203033190
ggplot(data=pca.data, aes(x=X, y=Y, label=Sample)) +
geom_text() +
xlab(paste("PC1 - ", pca.var.per[1], "%", sep="")) +
ylab(paste("PC2 - ", pca.var.per[2], "%", sep="")) +
theme_bw() +
ggtitle("My PCA Graph")
loading_scores <- pca$rotation[,1]
loading_scores
## gene1 gene2 gene3 gene4 gene5 gene6
## -0.10556159 0.10573872 -0.10544606 0.10431172 0.10610598 -0.10356908
## gene7 gene8 gene9 gene10 gene11 gene12
## 0.10626136 0.10637336 0.01508732 -0.10486604 0.10650050 -0.10560365
## gene13 gene14 gene15 gene16 gene17 gene18
## 0.09113077 0.10393936 0.10592585 -0.05975260 0.10635107 0.10410131
## gene19 gene20 gene21 gene22 gene23 gene24
## -0.10627027 -0.10632085 0.10611896 0.10116047 -0.10541809 0.09063823
## gene25 gene26 gene27 gene28 gene29 gene30
## -0.09844459 0.08499020 0.09874203 0.09975550 0.10629415 -0.10631525
## gene31 gene32 gene33 gene34 gene35 gene36
## 0.10639858 0.08432073 0.10599640 -0.09372548 -0.10628242 -0.08802190
## gene37 gene38 gene39 gene40 gene41 gene42
## -0.08916559 0.10258829 -0.10595666 -0.10630817 -0.09508663 -0.10002403
## gene43 gene44 gene45 gene46 gene47 gene48
## -0.10340193 0.10603196 -0.09757410 0.10623968 -0.10197771 0.10624879
## gene49 gene50 gene51 gene52 gene53 gene54
## -0.10594131 0.10467547 0.10464052 0.10227552 0.10572090 0.10631276
## gene55 gene56 gene57 gene58 gene59 gene60
## 0.10621612 -0.10640086 -0.10417734 0.10637836 0.10639660 0.10140712
## gene61 gene62 gene63 gene64 gene65 gene66
## -0.09836676 -0.10486284 0.10630409 0.10622580 0.07680151 -0.10644399
## gene67 gene68 gene69 gene70 gene71 gene72
## -0.10585202 0.07510557 -0.10542128 -0.10519254 0.10634360 0.01882213
## gene73 gene74 gene75 gene76 gene77 gene78
## -0.10609094 0.10574230 0.08444863 0.07929629 0.10646477 -0.09524695
## gene79 gene80 gene81 gene82 gene83 gene84
## -0.10606921 -0.10638588 -0.08600602 0.10351919 0.10636071 -0.10287625
## gene85 gene86 gene87 gene88 gene89 gene90
## 0.10173729 -0.10557624 -0.10620296 -0.03605430 -0.10604115 -0.10234180
## gene91 gene92 gene93 gene94 gene95 gene96
## 0.10568679 -0.10353843 0.10292872 0.10511157 -0.10572842 -0.10632064
## gene97 gene98 gene99 gene100
## 0.02623869 0.10607019 -0.09663728 -0.10563872
gene_scores <- abs(loading_scores) ## get the magnitudes
gene_score_ranked <- sort(gene_scores, decreasing=TRUE)
top_10_genes <- names(gene_score_ranked[1:10])
top_10_genes ## show the names of the top 10 genes
## [1] "gene11" "gene77" "gene66" "gene56" "gene31" "gene59" "gene80"
## [8] "gene58" "gene8" "gene83"
pca$rotation[top_10_genes,1] ## show the scores (and +/- sign)
## gene11 gene77 gene66 gene56 gene31 gene59
## 0.1065005 0.1064648 -0.1064440 -0.1064009 0.1063986 0.1063966
## gene80 gene58 gene8 gene83
## -0.1063859 0.1063784 0.1063734 0.1063607
tdata <- t(data.matrix)
heatmap(tdata)
